The fraud attempt may begin with an advertisement on a social platform, then move to a messaging application, before ending with a payment or financial transfer via another party. Between these stages, no single company has a complete view of everything that happens from the beginning of the process to its end.
This is the challenge that Meta puts at the heart of its approach to combating fraud, despite saying that it removed more than 159 million fraudulent ads around the world during 2025, and deleted 92 percent of them before users reported them. The company also removed 10.9 million accounts on Facebook and Instagram linked to criminal fraud centers, and reduced the rate of reporting fraudulent ads per view by more than 55 percent.
Despite this extent of monitoring, the company says that the problem is still evolving because fraudsters are constantly changing their methods and working across more than one platform and service, which makes discovering and disrupting the process more difficult for any party working alone.
Fraud is a multi-stage journey
In an exclusive interview with Asharq Al-Awsat, Anas Metwally, head of public policy for the Gulf Cooperation Council countries at Meta, explains that platforms may see how the fraudster is trying to reach the user, while financial institutions have greater visibility when implementing the payment or transfer process. Hence, sharing information between platforms, government agencies, financial institutions, and law enforcement agencies becomes an essential part of the confrontation.
In March 2026, Meta signed the “Industry Agreement to Combat Online Fraud” during a global summit at the United Nations Office on Drugs and Crime, along with 10 other companies, as part of an attempt to connect entities that see different parts of the fraud journey.
In Saudi Arabia: “Check before you react.”
In the Saudi market, Meta says the patterns it sees reflect the broader global challenge, with tactics including impersonation, fake offers, messages claiming to win prizes, and opportunities promising unrealistic financial returns. The company does not provide separate numbers on the volume of these activities within the Kingdom, but it links the launch of the “Check” campaign to the need to increase users’ ability to recognize warning signs and stop to check before interacting.
Meta launched the campaign in cooperation with the General Authority for Media Regulation, with the aim of helping users in Saudi Arabia identify, avoid, and report fraud attempts. The slogan is based on a simple behavior: “Check before you react,” meaning to wait and check before clicking on a link, sharing content, or sending information. During the campaign period, 10 Saudi content makers participate in providing practical stories and advice in Arabic, in an attempt to bring awareness closer to users’ daily experiences.
Platform responsibility and user awareness
Meta does not believe that user protection falls between the options of technology or awareness. According to Metwally, the company is investing in monitoring technologies supported by artificial intelligence, account protection, and enforcement procedures, but it considers awareness an additional layer because many fraudulent operations ultimately depend on creating urgency, exploiting trust, and pushing the user to act before verification.
The company also confirms that user reports do not only lead to reporting an individual case, but also help it identify new fraudulent methods, monitor potential gaps in protection methods, and understand how fraudsters’ tactics change more quickly, which can support the modernization of protection and response systems.
In-app protection tools
The protection tools that Meta refers to include Facebook warnings when clicking on links classified as unsafe, WhatsApp alerts when trying to log in from an unknown device, and the option to mute calls from unsaved numbers. The tools also include two-factor authentication, passkeys, a privacy check-up, and an account security check-up, along with a “fraud protection center,” which brings together fraud reporting and safety tips.
“Sago” for checking suspicious messages
Within the initiative, the “Sago” tool stands out, which is a chatbot developed by Mythos Labs and works via WhatsApp. The user can forward a suspicious message or send a screenshot to the robot, which will analyze the content and highlight indicators that help assess the possibility of it being linked to a fraud attempt. Meta offers it as a tool to help verify before interacting, within a broader system of protection methods.
As for advertisements, Meta says that it is expanding verification procedures for advertisers, especially in the highest-risk categories, given that verification helps increase transparency and limit attempts to present a misleading identity.
The company aims for 90 percent of its advertising revenues by the end of 2026 to come from verified advertisers, with this measure working alongside artificial intelligence monitoring, enforcement, reporting tools, and account protection.
How will the success of “Chick” be measured?
Metwally did not specify a declared digital goal for the campaign in his response to specific Saudi indicators, such as a decrease in exposure to fraud attempts, a decline in fraudulent accounts, or a change in reporting patterns. He stated that the primary goal is for users to become more aware of warning signs, more likely to stop and check before interacting, and more familiar with safety and reporting tools. The company describes this path as a long-term effort to promote a safe digital culture in Saudi Arabia.
Limits of current cooperation
Although “Meta” works globally with governments, financial institutions, law enforcement agencies, and sector partners to confront fraudulent networks, the “Shaik” campaign in Saudi Arabia is still, according to “Meta,” focused on awareness and digital culture. The company has not yet announced the expansion of the initiative locally into direct operational mechanisms with banks, telecommunications companies, or law enforcement agencies, but it indicates that cooperation across the broader system remains necessary because each party sees a different stage of the fraud process.
Here remains the most important challenge: If the fraud attempt can move from an advertisement to a message and then to a financial transaction in another service, the success of the confrontation will not only depend on the ability of one platform to delete an advertisement or close an account, but rather on the speed of linking signals between the various parties before the fraudulent path is complete and the loss reaches the user.
The global digital landscape is witnessing a historic and profound transformation in the way users access information, surpassing traditional search engines that have relied for decades on displaying a list of traditional links. At the heart of this radical change emerges a completely new concept known as “Generative Engine Optimization GEO,” which reformulates the rules of interaction between brands and companies with the target audience through generative artificial intelligence techniques and advanced smart systems that are now leading the technology sector.
“Generative SEO” is the set of strategies and advanced technologies aimed at ensuring that brands, products and company content appear within direct answers and intelligent summaries generated by artificial intelligence systems and search engines powered by large language models. Instead of directing the user to visit multiple sites to compare options and manual search, these modern systems extract satisfactory answers and present them in an integrated and accurate narrative form at the top of the search results, which makes being within this generative scope crucial for ambitious institutions.
From the ranking race to the accuracy of the answer
The fundamental differences between traditional “Search Engine Optimization” (Search Engine Optimization) and “Generative Search Engine Optimization” lie in the radical shift from ranking to direct answering. Whereas previously the focus was exclusively on keywords and building backlinks, and aiming for the site to appear in the first results to increase the number of clicks and visits, the modern approach relies on contextual reliability, cognitive depth, and the ability to provide accurate answers that the generative artificial intelligence algorithms understand and quote as a reliable reference within their final responses to users.
Why do non-compliant companies face significant decline?
Companies and institutions that neglect this new digital transformation are severely affected, as they face a noticeable and continuous decline in the rates of natural visits coming from search engines. As users become accustomed to getting comprehensive, direct, and concise answers from the AI assistant without having to browse traditional websites, companies and brands that do not appear in those smart summaries will gradually lose market share to competitors who are more proactive and compatible with modern standards.
The negative impact of the absence of “generative search engine optimization” strategies extends to weakening trust in the brand and eroding its leadership position within the industrial or commercial sector in which it operates. The failure of the company name to appear as a reliable primary reference when potential customers inquire about specific solutions, services or products gives an implicit impression of not keeping up with the times or lack of effectiveness and innovation, which automatically pushes users towards the alternative options recommended by artificial intelligence with absolute confidence and reassurance.
Requirements for compatibility with large language models
Successful and effective adaptation to generative SEO requires comprehensive and strategic re-engineering of digital content strategies to fully match the nature and workings of large linguistic models. Today, it is not enough to publish traditional articles that contain a typical repetition of keywords. Rather, great attention must be paid to providing content rich in reliable data, in-depth analysis, and direct and clear answers to complex questions that users usually ask in natural, conversational forms of inquiry.
Companies and institutions need to adopt accurate and advanced data structuring and provide clear and structured information that is easy for artificial intelligence algorithms to read and understand its context and meanings with extreme accuracy. This includes the use of advanced semantic markup, organizing complex information into tables and sequential logical steps, and providing clear and direct definitions of products and services that allow search systems to extract and reformulate them with ease and high reliability.
Artificial intelligence algorithms rely primarily and pivotally on multiple and diverse sources to verify the validity and strength of information before presenting it to the end user, which makes building a strong network of external digital signals extremely important. The presence of the company, its products, and its real customers’ evaluations regularly distributed across reliable platforms, news sites, and specialized forums doubles the chance that its artificial intelligence systems will be cited as a primary and exclusive source of the answer.
Credibility, transparency, and direct experience are pivotal and essential elements in the success of “generative search engine optimization” strategies, as large language models always prefer sources behind which are certified experts and real specialists in their fields. Companies should highlight the identities of content writers, reviewers, and specialists and link digital content to clear professional and academic records to ensure that submitted materials fall into highly reliable categories that generative search algorithms blindly trust.
The most prominent generative SEO tools and their capabilities
There are specialized software solutions that help institutions and companies measure their visibility and track their performance within these new generative environments. These modern platforms provide accurate insights and advanced capabilities to effectively monitor brand presence and optimize generative content strategies. Below we mention five leading tools and their basic capabilities:
* Profound AI:
- Description and capabilities: Designed specifically for software startups, it combines traditional SEO datasets and competitor research with AI insight tracking across multiple engines such as ChatGPT, Perplexity, Gemini, and Cloud.
- Benefits: It features a “Conversion Explorer” that automatically detects important queries based on a full site audit, relieving teams from entering queries manually, in addition to providing deep competitive intelligence.
* Scrunch tool:
- Description and Capabilities: A generative SEO and analytics platform that focuses on how AI systems describe and recommend brands across systems such as ChatGPT, Perplexity, and Gemini.
- Benefits: Go beyond passive reporting by integrating monitoring and insights with actionable content optimization recommendations and an agent experience platform to help mature growth teams improve their positioning.
* Peec AI:
Description and capabilities: A specialized platform designed to help software startups track and improve their visibility within large language modeling platforms.
- Benefits: Provides instant ease of use through automatic setup, generates a free AI insight report when you enter a website link and provides clear visibility scores, signal analysis and competitor comparison matrices.
* Semrush tool:
- Description and capabilities: An extension of traditional SEO infrastructure that integrates custom intelligent search tracking modules to monitor the performance of generative search engines.
- Benefits: Allows companies to track market share and brand mentions directly via search engines.
